def hist_compare_best(game,name='dense',num_games=100):
wins_list = []
losses_list = []
draws_list = []
best_wins = 0
best_net = 0
for net_no in range(1,11):
if best_net == 0:
player2 = Nets.Dense() # dense or conv
else:
player2 = Nets.Dense() # dense or conv
player2.load_state_dict(torch.load(name+'/'+name+str(int(best_net))+'.pth')) # dense or conv
player2.eval()
player1 = Nets.Dense() # dense or conv
player1.load_state_dict(torch.load(name+'/'+name+str(int(net_no))+'.pth')) # dense or conv
player1.eval()
print('Pitting',net_no-1,'and',net_no)
wins,draws,losses = pit_against_network(player1,player2,game,num_games)
print('wins:',wins)
print('draws:',draws)
print('losses:',losses)
if(wins>=best_wins):
best_wins = wins
best_net = net_no
print('Best Net:',best_net)
wins_list.append(wins)
draws_list.append(draws)
losses_list.append(losses)
plt.plot(wins_list,color='green')
plt.plot(losses_list,color='red',alpha=0.3)
plt.savefig('BestHistComp'+name+'.png')
import numpy as np
import torch
import Nets
from eval import pit_against_network, pit_human, hist_compare
from Connect4Game import Connect4Game
if __name__ == '__main__':
# initialize networks
net = Nets.Dense()
net.load_state_dict(torch.load('dense/dense9.pth'))
net.eval()
aux_net = Nets.Dense()
# initialize game
game = Connect4Game()
wins, draws, losses = pit_against_network(net, aux_net, game, 100)
print('Wins:', wins)
print('Losses:', losses)
print('Draws:', draws)
#pit_human(net,game)
#hist_compare(game,name='dense',num_games=100)